Early hematopoietic reconstitution after clinical stem cell transplantation: evidence for stochastic stem cell behavior and limited acceleration in telomere loss
Bibliographic record
Abstract
Our inability to purify hematopoietic stem cells (HSCs) precludes direct study of many aspects of their behavior in the clinical hematopoietic stem cell transplantation (HSCT) setting. We indirectly assessed stem/progenitor cell behavior in the first year after HSCT by examining changes in neutrophil telomere length, X-inactivation ratios, and cycling of marrow progenitors in 25 fully engrafted allogeneic HSCT recipients. Donors were sampled once and recipients at engraftment and 2 to 6 months and 12 months after HSCT. Telomere length was measured by an in-gel hybridization technique, X-inactivation ratios were measured by the human androgen receptor assay, and cell cycle status was determined by flow cytometric analysis of pyronin Y- and Hoechst 33342-stained CD34(+)CD90(+) and CD34(+)CD90(-) marrow cells. Compared with their donors, recipients' telomeres were shortened at engraftment (-424 base pairs [bp]; P <.0001), 6 months (-495 bp; P =.0001) after HSCT, and 12 months after HSCT (-565 bp; P <.0001). There was no consistent pattern of change in telomere length from 1 to 12 months after HSCT; marked, seemingly random, fluctuations were common. In 11 of 11 informative recipients, donor X-inactivation ratios were faithfully reproduced and maintained. The proportion of CD34(+)CD90(+) progenitors in S/G(2)/M was 4.3% in donors, 15.7% at 2 to 6 months (P <.0001) after HSCT, and 11.5% at 12 months after HSCT (P <.0001, versus donors; P =.04, versus 2-6 months). Cycling of CD34(+) CD90(-) progenitors was largely unchanged. We infer that (1) HSCT-induced accelerated telomere loss is temporary and unlikely to promote graft failure or clonal hematopoietic disorders and (2) the striking fluctuations in telomere length and variation in pattern of telomere loss reflect stochastic determination of HSC fate after HSCT.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".